Journal article
An empirically adjusted approach to reproductive number estimation for stochastic compartmental models: A case study of two Ebola outbreaks
Biometrics, Vol.72(2), pp.335-343
06/2016
DOI: 10.1111/biom.12432
PMID: 26574727
Abstract
The various thresholding quantities grouped under the "Basic Reproductive Number" umbrella are often confused, but represent distinct approaches to estimating epidemic spread potential, and address different modeling needs. Here, we contrast several common reproduction measures applied to stochastic compartmental models, and introduce a new quantity dubbed the "empirically adjusted reproductive number" with several advantages. These include: more complete use of the underlying compartmental dynamics than common alternatives, use as a potential diagnostic tool to detect the presence and causes of intensity process underfitting, and the ability to provide timely feedback on disease spread. Conceptual connections between traditional reproduction measures and our approach are explored, and the behavior of our method is examined under simulation. Two illustrative examples are developed: First, the single location applications of our method are established using data from the 1995 Ebola outbreak in the Democratic Republic of the Congo and a traditional stochastic SEIR model. Second, a spatial formulation of this technique is explored in the context of the ongoing Ebola outbreak in West Africa with particular emphasis on potential use in model selection, diagnosis, and the resulting applications to estimation and prediction. Both analyses are placed in the context of a newly developed spatial analogue of the traditional SEIR modeling approach.
Details
- Title: Subtitle
- An empirically adjusted approach to reproductive number estimation for stochastic compartmental models: A case study of two Ebola outbreaks
- Creators
- Grant D Brown - Department of Biostatistics, University of Iowa, Iowa City, Iowa, 52242, U.S.AJacob J Oleson - Department of Biostatistics, University of Iowa, Iowa City, Iowa, 52242, U.S.AAaron T Porter - Department of Applied Mathematics and Statistics, Colorado School of Mines, Golden, Colorado, 80401, U.S.A
- Resource Type
- Journal article
- Publication Details
- Biometrics, Vol.72(2), pp.335-343
- Publisher
- United States
- DOI
- 10.1111/biom.12432
- PMID
- 26574727
- ISSN
- 0006-341X
- eISSN
- 1541-0420
- Grant note
- DOI: 10.13039/100008893, name: The University of Iowa
- Language
- English
- Date published
- 06/2016
- Academic Unit
- Biostatistics
- Record Identifier
- 9983997314002771
Metrics
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